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Record W1902630259 · doi:10.1093/biolreprod/81.s1.105

Follicle Atresia Is Regulated by Fibroblast Growth Factor-18 in Cattle.

2009· article· en· W1902630259 on OpenAlexaffabout
Valério Marques Portela, Mariana Fernandes Machado, Paulo Bayard Dias Gonçalves, Gustavo Zamberlam, J. Buratini, Christopher A. Price

Bibliographic record

VenueBiology of Reproduction · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFibroblast Growth Factor Research
Canadian institutionsUniversité de MontréalCegep de Saint Hyacinthe
Fundersnot available
KeywordsBiologyParacrine signallingFollicleFolliculogenesisThecaFibroblast growth factorInternal medicineEndocrinologyOogenesisOocyteCorpus luteumCell biologyOvaryReceptorGeneticsEmbryogenesisEmbryo

Abstract

fetched live from OpenAlex

Understanding the paracrine events that regulate fertility in the cow is necessary not only because of the agricultural importance of this species, but also its potential use as a model for humans. Fibroblast growth factors (FGF) and their receptors are involved in the paracrine modulation of ovarian function. For example, FGF2, 7 and 10 inhibit estradiol secretion by granulosa cells in vitro. Another member of this family, FGF8, is an oocyte-derived protein that modulates glycolysis in cumulus cells. FGFs are grouped into subfamilies of closely-related proteins, and FGF18 is in the same subfamily as FGF8 and has also been detected in mouse oocytes. The existance of a subfamily of FGFs that are specifically derived from the oocyte are potentially interesting paracrine regulators of fertility. The objectives of the present study were to localize the expression of FGF18 in the bovine follicle, to gain insight into the control of FGF18 expression and to identify potential actions of FGF18 in the follicle. Bovine ovaries were obtained from an abattoir for localizing expression patterns by real-time PCR and immunohistochemistry. FGF18 mRNA was not detected in pooled oocytes by PCR, but was present in isolated theca and granulosa cells (GC), and protein was detected in the follicle wall by immunohistochemistry. Expression during follicle growth was measured by collecting the two largest follicles per cow at defined stages of the first follicle wave. The follicles were classified as dominant and subordinate according to estradiol levels in follicular fluid and aromatase mRNA abundance in GC. FGF18 mRNA abundance in both GC and theca cells was higher in subordinate follicles compared with dominant follicles (P<0.05). To determine regulation and function of FGF18, granulosa cells were isolated from 5-8 mm follicles and employed in an estrogenic, serum-free culture system. In vitro, FGF18 expression was down-regulated by IGF1, insulin, FGF2, FGF10 (P<0.05) in GC. In further experiments, the addition of graded doses of FGF18 (0, 1, 10, 100 ng/ml) to GC in culture inhibited estradiol secretion and abundance of mRNA encoding the estrogenic enzymes aromatase and 17β-hydroxysteroid dehydrogenase (17βHSD), and the FSH receptor. Progesterone secretion was also inhibited, which was associated with decreased abundance of mRNA encoding CYP11, StAR and 3βHSD. Assessment of apoptosis by flow cytometry showed that FGF18 significantly increased the proportion of apoptotic cells, and this was accompanied by decreased abundance of mRNA encoding antiapoptotic and proliferation genes (MIF, RFC4 and GADD45B). In summary, FGF18 is expressed in GC and theca cells but--in contrast to the subfamily prototype, FGF8--not in oocytes in cattle. As FGF18 expression is increased in atretic follicles, and as FGF18 protein inhibits estradiol secretion and induces apoptosis, we conclude that FGF18 plays a role in follicular atresia. Supported by NSERC Canada, CNPq and FAPESP, Brazil. (platform)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.280
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2009
Admission routes2
Has abstractyes

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